MDMU ProMatch™ is a data-driven provider matching and patient navication solution that helps connect people with the right providers based on their unique needs. ProMatch enhances accuracy by analyzing factors such as specialty, location, availability, and compatibility preferences to deliver personalized recommendations. By integrating with existing provider directories and scheduling systems, ProMatch eliminates guesswork, reduces mismatches, and improves patient access to care. Its intelligent matching capabilities support marketing, call centers, and digital front doors, ensuring a seamless patient experience while optimizing provider utilization and engagement.

MD MatchUp helps health systems, payers, and medical groups keep provider data accurate and connect patients with the right doctors. With patient-provider matching and better provider directories, more patients find and schedule care while fewer appointments go to waste. MD MatchUp works with existing EHRs and systems to improve efficiency, boost patient satisfaction, and increase revenue—all while making healthcare access easier for everyone.

Without Hyro, health system call centers are reaching the burnout threshold too quickly. That’s when the perfect storm of missed calls, long wait times and poor user experience hits hard, ultimately causing patient churn and lost revenues. With Hyro, call center capacity is a non-issue, with 65-85% of calls being automatically deflected or resolved end-to-end, and the remainder of calls being quickly and accurately routed to the right departments.

It's an ever-clean filter you never need to change – Hyro has a three-pronged system to sorting call volume, automating routine calls without human intervention, directing complex calls to the right agent, and deflecting simple calls to SMS for self-service.

Smart Routing:

Navigate calls to the accurate source of support with natural language understanding (NLU)- based smart routing. Instantly match and transfer patient queries to the right service departments, skipping complicated audio menus and lengthy wait times in the process.

End-to-End Resolution:

Automate key digital services from start to finish with conversational AI end-to-end resolution. Solve routine requests such as physician scheduling, paying bills and getting answers to critical questions, without a human in the loop.

SMS Deflection/ Call-to-Text:

Shield overloaded call center teams from repetitive tasks with SMS Deflection (Call-to-Text). Funnel patients to self-serve with the resources you’ve already invested in, directing them to patient portals, FAQ pages, chat solutions and mobile app features.

Benefits:

• 3-10 day deployment
• Zero client-side maintenance
• 60-85% deflection/ resolution of calls and messages
• 5x Average Handle Time
• 99% reduction in Average Hold Time
• Pre-loaded skills, like scheduling and routing
• Proprietary natural language engine that adapts to patients' dialects, phrasing, sentiment and more
• Integrations with Epic EMR, Salesforce, and major telephony providers like Cisco, NICE, Genesys and Twilio

Hyro is a plug & play conversational AI platform enabling healthcare enterprises to easily supercharge patient experiences with voice & text capabilities across all their digital channels.

MDMU ProMatch™ enhances provider search, with a data-driven personal matching system—offering a consumer-friendly, EHR-agnostic solution for improved patient access, engagement and satisfaction.

1. PATIENT-PROVIDER MATCHING: Unlike EHRs, which primarily store provider data, ProMatch uses first-party data from patients and providers to personalize provider recommendations based on needs, preferences, compatibility and availability.

2. ENHANCED PROVIDER SEARCH & NAVIGATION: ProMatch offers advanced search capabilities with dynamic filtering, geolocation-based navigation, and intelligent ranking, whereas EHRs often have limited or static provider directories.

3. CONSUMER-CENTRIC EXPERIENCE: EHRs are designed for clinical workflows, while ProMatch prioritizes a seamless, intuitive consumer experience with self-service tools and guided interactions that result in more personalization and higher satisfaction. 

4. SCHEDULING INTEGRATION: ProMatch is vendor agnostic and can integrate with and display information from multiple scheduling platforms.

5. CROSS-PLATFORM COMPATIBILITY: ProMatch is EHR-agnostic, integrating with multiple systems to unify provider data, while EHR-based solutions are typically restricted to their native ecosystem.

6. ANALYTICS & ENGAGEMENT INSIGHTS: ProMatch delivers in-depth analytics on provider search trends, patient preferences, and engagement data, whereas EHRs primarily focus on clinical documentation and operational data.

MDMU ProMatch™ ensures accurate, first-party consumer and provider data with EHR-agnostic integration, structured search, geolocation, and seamless self-service selection—streamlining patient access and enterprise data management.

1. FIRST-PARTY DATA ACCURACY: Unlike competitors relying on third-party sources, ProMatch ensures high-quality data directly from consumers and providers, themselves—reducing inaccuracies and outdated information.

2. EHR-AGNOSTIC & MULTI-SYSTEM INTEGRATION: While some solutions are tied to specific EHRs, ProMatch integrates across multiple platforms, ensuring flexibility and consistency in provider data.

3. COMPREHENSIVE PROVIDER SEARCH & NAVIGATION: ProMatch enables structured and personalized provider search with robust filtering, specialty-based navigation, and geolocation capabilities, making it easier for patients to find the right care at the right time.

4. SELF-SERVICE PROVIDER SELECTION: ProMatch allows patients to independently navigate provider options within a network’s ecosystem, improving access and reducing administrative burdens.

5. CARE OPTION AGGREGATION & ENGAGEMENT: While competitors focus primarily on directories, ProMatch supports personalized patient engagement by centralizing provider information and guiding patients toward appropriate care options

6. ENTERPRISE-GRADE DATA MANAGEMENT: Designed for scalability, ProMatch ensures provider data remains consistent across marketing, credentialing, and operational teams, streamlining updates and minimizing discrepancies.

Hyro layers on top of EHR functionality, adding natural language understanding to pre-existing workflows and use cases across Epic, Cerner and Athena.

Our main competitors, such as Syllable and Nuance, focus on intent-based voice solutions. Intent, within the conversational AI space, usually means "if X then Y". For example, if AVIA says "red" then stop. We know that conversations need to be more flexible than a rigid flow chart of intents, so Hyro invented a new language-based approach called Adaptive Communications, which uses a knowledge graph, computational linguistics and natural language understanding to simplify and speed up deployment processes. Because of our approach, health systems do not need to constantly update their voice interfaces based on ever-changing content. It also means that typical challenges with conversational AI, including adding new use cases to existing deployments, are nullified with the ability to layer on new data without retraining the model. Ultimately, the time and cost saved by switching from intent-based to language-based is what drove Intermountain Healthcare, Baptist Health, Novant Health and plenty of other health systems to Adaptive Communications.

Unique Benefits: 

• No-code, effortless deployment, and maintenance that doesn’t require any playbooks or training data
• Voice AI that adjusts to changes in context
• Fast automation of dozens of customized use cases and skills simultaneously
• Industry-leading understanding rate at an average of 85-90%
• Seamless live handoff between AI and agents on Cisco, Genesys, NICE, Twilio and more
• Automatic 24/7 scraping of data sources including websites, EMRs/ CRMs, APIs, and client databases
• Real-time dashboard with insights (trends, keywords, and metrics) that helps to optimize digital services
• Explainability that allows health systems to understand why/how AI provides all outputs